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We introduce a machine learning workflow to search for, identify, and meaningfully triage videos and images of munitions, weapons, and …
Recent advances have made it possible to create deep complex-valued neural networks. Despite this progress, the potential power of …
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here …
We propose a Class-Based Styling method (CBS) that can map different styles for different object classes in real-time. CBS achieves …
Compositional Pattern Producing Networks (CPPNs) are differentiable networks that independently map (x, y) pixel coordinates to (r, g, …
In this work, we improve upon the stepwise analysis of noisy iterative learning algorithms initiated by Pensia, Jog, and Loh (2018) and …
Here we present a new method of estimating global variations in outdoor PM2.5 concentrations using satellite images combined with …
Recent advances in variational inference enable the modelling of highly structured joint distributions, but are limited in their …
Metric-based meta-learning techniques have successfully been applied to few-shot classification problems. In this paper, we propose to …
Deep learning has mainly thrived by training on large-scale datasets. However, for continual learning in applications such as robotics, …